Embracing Project Optimus: Can We Leverage Evolutionary Theory to Optimize Dosing in Oncology?

Overview

Journal Pharm Res

Specialties Pharmacology
Pharmacy

Date 2022 Sep 2

PMID 36056271

Authors

Timothy Qi

Tyler Dunlap

Yanguang Cao

Affiliations

Soon will be listed here.

Abstract

Project Optimus is a US Food and Drug Administration (FDA) initiative to reform dose selection in oncology drug development. Here, we focus on tumor evolution, a broadly observed phenomenon that invariably leads to therapeutic failure and disease relapse, and its effect on the exposure-response (E-R) relationships of oncology drugs. We propose a greater emphasis on tumor evolution during clinical development to facilitate the selection of optimal doses for molecularly targeted therapies and immunotherapies in oncology.

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References

Poels K, Schoenfeld A, Makhnin A, Tobi Y, Wang Y, Frisco-Cabanos H . Identification of optimal dosing schedules of dacomitinib and osimertinib for a phase I/II trial in advanced EGFR-mutant non-small cell lung cancer. Nat Commun. 2021; 12(1):3697. PMC: 8211846. DOI: 10.1038/s41467-021-23912-4. View

Gatenby R, Silva A, Gillies R, Frieden B . Adaptive therapy. Cancer Res. 2009; 69(11):4894-903. PMC: 3728826. DOI: 10.1158/0008-5472.CAN-08-3658. View

Zhou J, Liu Y, Zhang Y, Li Q, Cao Y . Modeling Tumor Evolutionary Dynamics to Predict Clinical Outcomes for Patients with Metastatic Colorectal Cancer: A Retrospective Analysis. Cancer Res. 2019; 80(3):591-601. PMC: 7002273. DOI: 10.1158/0008-5472.CAN-19-1940. View

Cremolini C, Rossini D, DellAquila E, Lonardi S, Conca E, Del Re M . Rechallenge for Patients With RAS and BRAF Wild-Type Metastatic Colorectal Cancer With Acquired Resistance to First-line Cetuximab and Irinotecan: A Phase 2 Single-Arm Clinical Trial. JAMA Oncol. 2018; 5(3):343-350. PMC: 6439839. DOI: 10.1001/jamaoncol.2018.5080. View

Savarese D, Hsieh C, Stewart F . Clinical impact of chemotherapy dose escalation in patients with hematologic malignancies and solid tumors. J Clin Oncol. 1997; 15(8):2981-95. DOI: 10.1200/JCO.1997.15.8.2981. View

Woolston A, Khan K, Spain G, Barber L, Griffiths B, Gonzalez-Exposito R . Genomic and Transcriptomic Determinants of Therapy Resistance and Immune Landscape Evolution during Anti-EGFR Treatment in Colorectal Cancer. Cancer Cell. 2019; 36(1):35-50.e9. PMC: 6617392. DOI: 10.1016/j.ccell.2019.05.013. View

Garcia-Murillas I, Chopra N, Comino-Mendez I, Beaney M, Tovey H, Cutts R . Assessment of Molecular Relapse Detection in Early-Stage Breast Cancer. JAMA Oncol. 2019; 5(10):1473-1478. PMC: 6681568. DOI: 10.1001/jamaoncol.2019.1838. View

Nowell P . The clonal evolution of tumor cell populations. Science. 1976; 194(4260):23-8. DOI: 10.1126/science.959840. View

Avanzini S, Kurtz D, Chabon J, Moding E, Hori S, Gambhir S . A mathematical model of ctDNA shedding predicts tumor detection size. Sci Adv. 2020; 6(50). PMC: 7732186. DOI: 10.1126/sciadv.abc4308. View

10.

Weber S, van der Leest P, Donker H, Schlange T, Timens W, Tamminga M . Dynamic Changes of Circulating Tumor DNA Predict Clinical Outcome in Patients With Advanced Non-Small-Cell Lung Cancer Treated With Immune Checkpoint Inhibitors. JCO Precis Oncol. 2022; 5:1540-1553. DOI: 10.1200/PO.21.00182. View

11.

Zhou J, Li Q, Cao Y . Spatiotemporal Heterogeneity across Metastases and Organ-Specific Response Informs Drug Efficacy and Patient Survival in Colorectal Cancer. Cancer Res. 2021; 81(9):2522-2533. PMC: 8137573. DOI: 10.1158/0008-5472.CAN-20-3665. View

12.

Boumahdi S, de Sauvage F . The great escape: tumour cell plasticity in resistance to targeted therapy. Nat Rev Drug Discov. 2019; 19(1):39-56. DOI: 10.1038/s41573-019-0044-1. View

13.

Holderfield M, Deuker M, McCormick F, McMahon M . Targeting RAF kinases for cancer therapy: BRAF-mutated melanoma and beyond. Nat Rev Cancer. 2014; 14(7):455-67. PMC: 4250230. DOI: 10.1038/nrc3760. View

14.

Iams W, Kopparapu P, Yan Y, Muterspaugh A, Zhao Z, Chen H . Blood-Based Surveillance Monitoring of Circulating Tumor DNA From Patients With SCLC Detects Disease Relapse and Predicts Death in Patients With Limited-Stage Disease. JTO Clin Res Rep. 2021; 1(2):100024. PMC: 8474488. DOI: 10.1016/j.jtocrr.2020.100024. View

15.

Kawakatsu S, Bruno R, Kagedal M, Li C, Girish S, Joshi A . Confounding factors in exposure-response analyses and mitigation strategies for monoclonal antibodies in oncology. Br J Clin Pharmacol. 2020; 87(6):2493-2501. DOI: 10.1111/bcp.14662. View

16.

Zhang J, Cunningham J, Brown J, Gatenby R . Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer. Nat Commun. 2017; 8(1):1816. PMC: 5703947. DOI: 10.1038/s41467-017-01968-5. View

17.

Almodovar K, Iams W, Meador C, Zhao Z, York S, Horn L . Longitudinal Cell-Free DNA Analysis in Patients with Small Cell Lung Cancer Reveals Dynamic Insights into Treatment Efficacy and Disease Relapse. J Thorac Oncol. 2017; 13(1):112-123. PMC: 5827950. DOI: 10.1016/j.jtho.2017.09.1951. View

18.

Jain R, Lee J, Hong D, Markman M, Gong J, Naing A . Phase I oncology studies: evidence that in the era of targeted therapies patients on lower doses do not fare worse. Clin Cancer Res. 2010; 16(4):1289-97. PMC: 2822881. DOI: 10.1158/1078-0432.CCR-09-2684. View